Hemorrhagic stroke accounts for up to 20% of all stroke cases, and requires a treatment pathway drastically different to ischemic stroke. Prompt triage is therefore crucial and often only attainable with neuroimaging for intracranial hemorrhage (ICH) evaluation, for which MDCT is the frontline modality. Availability of ICH dedicated imaging in the pre-hospital setting, with portable CT systems, would facilitate early ICH diagnosis. However, current CT or cone-beam CT (CBCT) approaches often use conventional x-ray sources mounted on a rotating gantry limiting their minimum weight and footprint. Recent advances on cold-cathode, compact x-ray sources, based on carbon nanotube (CNT) technology, enable the development of ultra-compact designs based on source-array arrangements on stationary configurations. However, such geometrical arrangements show limited angular sampling, and sparse, non-stationary, volume sampling.In this work we present first investigation of geometric configuration and effects of 3D sampling pertinent to the task of ICH detection on an ultra-portable stationary CBCT for ICH imaging. The baseline configuration included 31 CNT sources on a curved array illuminating a curved panel detector (871 mm length), on a compact geometrical configuration (SDD = 690 mm). Metrics of sampling completeness, sampling density, and MTF shape and band-width integral were explored for configurations varying in source angular span (30°-170°), source array and detector curvature radius (250 mm to flat), use of 2D matrix source arrangements, and multi-acquisition protocols. The results show that sufficient sampling and resolution can be achieved with a combination of moderate curvature (~450 mm radius) of the source array and detectors, with better sampling properties for approximately matched curvature radii (up to 30% BWI improvement). Improved image quality was demonstrated with configurations featuring matrix source arrangements in combination with multi-acquisition protocols (around a 6% of improvement in sampling completeness).

Tomographic systems based on stationary arrangements of compact x-ray sources coupled to curved panel detectors have shown great potential for point-of-care brain imaging, but suffer from large, non-isotropic x-ray scatter. This work presents an adaptive kernel strategy to efficiently estimate scatter in stationary multi-source CT. The adaptive scatter estimation handles non-circular geometries, by the addition of pre- and post-processing steps to projection domain scatter estimators. The method was calibrated and evaluated on simulated data for a previously presented system with 31 x-ray sources on a circular arc coupled to a curved detector. Further assessment was obtained on experimental data obtained with an imaging testbench including a compact CNT-based x-ray source and simulating the scanner geometry. The method achieved accurate air-normalized scatter distributions across x-ray source positions and detector pixels, yielding a mean absolute error of 1.98𝑥10−3 with respect to the Monte-Carlo ground truth. Air-gap compensation had the largest impact on final accuracy. Image quality for simulated data showed consistent mitigation of scatter artifacts and reduction in non-uniformity from NU = 109 HU to 24 HU, with comparable performance for variations in cranium size, ranging in length from 161 mm (NU =14 HU) to 246 mm (NU = 15 HU). The experimental data showed comparable performance with error attributable to slight simulation infidelity. This work presents an adaptive approach to scatter compensation in multi-source, non-circular geometries using warping and weighting operations coupled to kernel-based scatter estimation on a virtual circular geometry, with immediate extension to other projection-based scatter compensation strategies.

Introduction: Patients with stroke in rural and remote areas have limited access to time-critical stroke care and have worse outcomes. Mobile stroke units (MSUs) are increasingly used worldwide to deliver prehospital stroke care, improving treatment times. However, current brain scanners are too large, heavy, and costly to be used in standard ambulances to access rural regions. The Micro-X solution is a fixed gantry computed tomography (CT) device, using unique cold-cathode technology, in which microscopic carbon nanotubes emit electrons instantaneously when voltage is applied, without heat production, instead of the heated tungsten filament used in conventional CT. This novel technology reduces size and weight, enabling development of a novel CT scanner weighing under 50 kg, a ten-fold reduction compared to the scanner currently used in most MSUs. Methods: In partnership with the Australian Stroke Alliance, Micro-X is developing a novel lightweight brain scanner for use in ambulances. Based on data from an early prototype cadaver study, we are undertaking further validation studies, including a two-part preclinical study: (1) phantom study using 4 phantoms (CATphan, anthropomorphic, Jaszczak SPECT, and Nuclear Medicine); and (2) subsequent cadaver study, scanning cadavers within 24h of death, compared to standard CT. Results: The early prototype cadaver study demonstrated feasibility, including identification of lateral and third ventricles when compared to concurrent CT. Through technical improvements in hardware and software, including improved scanner geometry and algorithm development, the planned phantom study will provide data on contrast resolution, quantitative spatial resolution, identification of anatomical structures, and haemorrhage detection compared with conventional CT. The subsequent cadaver study will provide further validation on anatomy identification and artifact reduction and ensure whole-brain coverage. Conclusion: Preclinical evaluation of this novel lightweight technology compared with conventional CT will provide technical assessment and image validation. This will provide diagnostic confidence to perform pilot in-vivo studies, with the potential to revolutionise prehospital stroke care.